计算机教学模式改革探究

计算机教学既要适应科技的发展和社会的需求,又要考虑现今受教育对象的特点。随着我国经济的迅速发展,计算机应用基础知识和基本技能是21世纪新型人才知识结构的重要组成部分,也是各个学校一门重要的基础课程。本文主要以加强学生的计算机动手能力和创新能力为目的,探讨了计算机教学模式改革,提高多媒体教学效率的几种途径。     

高职院校计算机课程教学方法探讨

现在随着计算机的不断普及,大学生的计算机基础素质也越来越高。在新形势的要求下,为了达到教学目的,保证教学的质量,作为大学阶段的计算机课程必须与时俱进,针对新形势、新情况,不断探索和改革教学内容及教学方式方法。本文将对计算机教学过程中教学方法的问题进行探讨研究,并根据实践经验提出几点建议。     

Patchy solution of a Francis–Byrnes–Isidori partial differential equation

The solution to the nonlinear output regulation problem requires one to solve a first‐order partial differential equation, known as the Francis–Byrnes–Isidori equations. In this paper, we propose a method to compute approximate solutions to the Francis–Byrnes–Isidori equations when the zero dynamics of the plant are hyperbolic and the exosystem is two dimensional. With our method, we are able to produce approximations that converge uniformly to the true solution. Our method relies on the periodic nature of two‐dimensional analytic center manifolds. Copyright © 2012 John Wiley & Sons, Ltd.     

Segmentation of the left ventricle in cardiac cine MRI using a shape-constrained snake model

Segmentation of the left ventricle (LV) is a hot topic in cardiac magnetic resonance (MR) images analysis. In this paper, we present an automatic LV myocardial boundary segmentation method using the parametric active contour model (or snake model). By convolving the gradient map of an image, a fast external force named gradient vector convolution (GVC) is presented for the snake model. A circle-based energy is incorporated into the GVC snake model to extract the endocardium. With this prior constraint, the snake contour can conquer the unexpected local minimum stemming from artifacts and papillary muscle, etc. After the endocardium is detected, the original edge map around and within the endocardium is directly set to zero. This modified edge map is used to generate a new GVC force filed, which automatically pushes the snake contour directly to the epicardium by employing the endocardium result as initialization. Meanwhile, a novel shape-similarity based energy is proposed to prevent the snake contour from being strapped in faulty edges and to preserve weak boundaries. Both qualitative and quantitative evaluations on our dataset and the publicly available database (e.g. MICCAI 2009) demonstrate the good performance of our algorithm.     

Using task migration to improve non-contiguous processor allocation in NoC-based CMPs

In this paper, a processor allocation mechanism for NoC-based chip multiprocessors is presented. Processor allocation is a well-known problem in parallel computer systems and aims to allocate the processing nodes of a multiprocessor to different tasks of an input application at run time. The proposed mechanism targets optimizing the on-chip communication power/latency and relies on two procedures: processor allocation and task migration. Allocation is done by a fast heuristic algorithm to allocate the free processors to the tasks of an incoming application when a new application begins execution. The task-migration algorithm is activated when some application completes execution and frees up the allocated resources. Task migration uses the recently deallocated processors and tries to rearrange the current tasks in order to find a better mapping for them. The proposed method can also capture the dynamic traffic pattern of the network and perform task migration based on the current communication demands of the tasks. Consequently, task migration adapts the task mapping to the current network status. We adopt a non-contiguous processor allocation strategy in which the tasks of the input application are allowed to be mapped onto disjoint regions (groups of processors) of the network. We then use virtual point-to-point circuits, a state-of-the-art fast on-chip connection designed for network-on-chips, to virtually connect the disjoint regions and make the communication latency/power closer to the values offered by contiguous allocation schemes. The experimental results show considerable improvement over existing allocation mechanisms.     

Nonlinear model predictive control with relevance vector regression and particle swarm optimization

In this paper, a nonlinear model predictive control strategy which utilizes a probabilistic sparse kernel learning technique called relevance vector regression （RVR） and particle swarm optimization with controllable random exploration velocity （PSO-CREV） is applied to a catalytic continuous stirred tank reactor （CSTR） process. An accurate reliable nonlinear model is first identified by RVR with a radial basis function （RBF） kernel and then the optimization of control sequence is speeded up by PSO-CREV. Additional stochastic behavior in PSO-CREV is omitted for faster convergence of nonlinear optimization. An improved system performance is guaranteed by an accurate sparse predictive model and an efficient and fast optimization algorithm. To compare the performance, model predictive control （MPC） using a deterministic sparse kernel learning technique called Least squares support vector machines （LS-SVM） regression is done on a CSTR. Relevance vector regression shows improved tracking performance with very less computation time which is much essential for real time control.     

Uplink resource allocation in OFDMA system using distributed antennas

In this article, we investigate uplink resource allocation in orthogonal frequency division multiple access （OFDMA） systems that use distributed antennas. The multiple distributed receiving antennas motivate us to exploit the spatial diversity to maximize the achievable rate of the system. Given constraints on the subcarrier allocation and the power limit of each user equipment （UE）, a mixed-integer optimization problem is formulated. We first propose a centralized greedy algorithm to find the maximum achievable rate of the system. Then a heuristic algorithm is proposed that can be implemented in a distributed manner. Simulation results show that the heuristic algorithm can approximately achieve the maximum achievable rate of the system and result in significant system performance improvement over the approach assigning one user to each subcarrier.     

Joint relay selection and power allocation for amplify-and-forward two-path relaying networks

This paper presents a joint relay selection and power allocation scheme for amplify-and-forward two-path relaying networks,in which diferent relay nodes forward information symbols alternatively in adjacent time slots.Our approach is based on the maximization of the received signal-to-noise ratio under total power consumption by the transmission of the symbol.We show that in spite of inter-relay interferences,the maximization problem has a closed-form solution.Simulation results explicitly indicate that the performance of proposed approach outmatches the existing methods including equal power allocation and one-path relaying.     

Dynamically reconfigurable radio-over-fiber network with medium access control protocol to provide network access to train passengers

An innovative dynamically reconfgurable radio-over-fber(RoF)network equipped with an intelligent medium access control(MAC)protocol is proposed to provide broadband access to train passengers in railway high-speed mobile applications.The proposed RoF network architecture is based on a reconfgurable control station and remote access unit(RAU)that is equipped with a fxed flter and tunable flter.The proposed hybrid frequency-division multiplexing/time division multiple access(FDM/TDMA)based MAC protocol realizes failure detection/recovery and dynamic wavelength allocation to remote access units.Simulation result shows that with the proposed MAC protocol,the control station can detect failures and recover and dynamic wavelength allocation can increase the wavelength resource utilization to maintain network performance.